Provenance is about describing the creation, modification history, ownership and generally any other aspect that may significantly influence the lifetime of data and data-sets. In many scientific environments, data-driven analyses are now performed on large volumes of data and multiple sources yielding sophisticated methods. The manual maintenance of pertinent provenance information such as what methods, what parameters, who and when created and/or modified, is not only time consuming but also error-prone. The systematic and timely capture of the above information may accurately keep track of the various stages that data go through and help precisely articulate the processes used. The provenance of data and processes is expected to help validate and re-produce experiments as well as to greatly assist in the interpretation of data-analyses outcomes. These are all crucial for knowledge discovery.

While provenance plays an important role in the scientific study at large and a number of systems have already furnished limited related functionalities, provenance has only recently attracted the attention of computer scientists. Provenance poses many fundamental challenges, such as performance, scalability, and interoperability in various environments.

The examination of data and process provenance is a multi-disciplinarily activity. Among others, it involves data management, software engineering, workflow system, information retrieval, web service, and security research. At the same time, it also requires understanding of problems from specific scientific domains to better address corresponding requirements. The main objective of this workshop is to bring together researchers from multiple disciplines who have confronted and dealt with provenance-related issues and exchange ideas and/or experiences. The workshop is also expected to help shape a provenance research agenda in the years ahead.

Topics of interest include, but are not limited to:

* Data lineage

* Architecture and prototype
* Provenance modelling
* Information management for provenance data
* Provenance querying

* Provenance annotation
* Security and privacy for provenance information
* Provenance analytics, mining and visualization
* Provenance algorithms
* Reasoning over provenance
* Provenance ontology

* Interoperability
* Trust
* Provenance and semantic web technology
* Integration of provenance
* User interface

* Provenance application and case study
* Provenance in practice

Important Dates

* Full papers due: January 20, 2009
* Notification to authors: February 28, 2009
* Camera-ready due: March 15, 2009
* Workshop: April 20, 2009